Introduction

BDSI R Training I

Emi Tanaka

Biological Data Science Institute

2nd November 2023

Welcome 👋

Teaching team

Dr. Emi Tanaka

Dr. Jon Roco

Dr. Terry Neeman
  • Who are you?
    • Introduce yourself to people around you
      • What do you do at ANU?
      • What interests do you have? Etc.

Workshop materials

All materials will be hosted at
https://anu-bdsi.github.io/training-R1/

Learning objectives

Overall goal

Develop skills to work with your research data using R

Today:

  • Setting up your data project (R project, folder structure)
  • Reading data into R (csv and xlsx)
  • The basics of R programming (atomic vectors, lists, data.frame, functions)
  • Computing simple numerical summaries of your data in R
  • Troubleshooting and producing minimal reproducible examples with reprex

What is R?

  • R is a programming language predominately for data analysis
  • RStudio Desktop is an integrated development environment (IDE) that helps you to use R
  • R packages are community developed extensions to R (much like apps on your mobile)
  • The Comprehensive R Archive Network (CRAN) is a volunteer maintained repository that hosts submitted R packages that are approved (much like an app store)
    • There are close to 20,000 packages available on CRAN
    • The qualities of R packages vary
  • There are other repositories that host R packages, e.g. Bioconductor for bioinformatics (we won’t cover this)

How to use R?

  • RStudio Desktop (or RStudio IDE) is the most common way to use R

  • You can type operations directly into the Console pane

Why learn R?

  • R is one of the top programming languages for statistics or data science
  • R was developed by statisticians for statisticians
  • R has an active and friendly community
  • R is a free and open source software (FOSS)
    • free = money is not a barrier to use it
    • open source software = transparency